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[{"key": "dc.contributor.advisor", "value": "Cochez, Michael", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Terziyan, Vagan", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Mwakyusa, Phesto Enock", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2017-10-23T13:27:04Z", "language": "", "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2017-10-23T13:27:04Z", "language": "", "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2017", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.other", "value": "oai:jykdok.linneanet.fi:1726691", "language": null, "element": "identifier", "qualifier": "other", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/55667", "language": "", "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "This thesis analyzes approaches to generate semantic annotations on patent records,\r\nas well as on other structured data, by relying on the structure and semantic representation\r\nof documents. Information in patent records reflects how real-world technologies evolve,\r\nand the approximately 3 million annual new patent applications capture the global inventive\r\nfrontier. The volume of this information is too big to be effectively analyzed purely with\r\nhuman effort, necessitating Big data approaches to analyze it with computer aided tools and\r\ntechniques. Big data is a term that describes a massive volume of structured, semi structured\r\nand unstructured data that is so large to the point that it is difficult to process using tradi-\r\ntional database and software tools and techniques. Currently, technical information, such as\r\npatents, is typically stored in data repositories that do not support advanced Big data methods\r\nto structure and interpret documents. In the emerging Semantic technology, annotation, Web\r\nsearch, as well as interpretation and aggregation can be addressed by ontology-based seman-\r\ntic annotation. This thesis examines semantic annotation and other Big data methodologies,\r\nand their basic requirements, and reviews the current generation of semantic annotation and\r\nother Big data systems. As a use case, this thesis demonstrates how semantic annotation\r\nand other Big data techniques are employed to enhance the human processes whereby peo-\r\nple retrieve information, carry out analysis or discovery within a large collection of patent\r\ninformation.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Semanttinen annotaatio ja big data-menetelmi\u00e4 patentti-informaation prosessointiin. \r\n\r\nT\u00e4m\u00e4 tutkielma analysoi miten luoda semanttisia annotaatioita\r\npatenttietueisiin, tai muuhun ei-strukturoituun dataa, hy\u00f6dynt\u00e4m\u00e4ll\u00e4 tietueiden rakennetta\r\ntai semanttista representaatiota. Patenttitietueet sis\u00e4lt\u00e4v\u00e4t kokonaisuutena informaation\r\nsiit\u00e4, miten reaalimaailman teknologiat kehittyv\u00e4t ja muuttuvat, ja vuosittain globaalisti\r\njulkaistavat noin 3 miljoonaa uutta patenttihakemusta kuvaavat hyvin globaalin keksint\u00f6rintaman\r\nkehityst\u00e4. T\u00e4m\u00e4 informaatio on volyymiltaan liian laaja, jotta sit\u00e4 voisi tehokkasti\r\nanalysoida ja k\u00e4sitell\u00e4 puhtaasti ihmisvoimin. T\u00e4st\u00e4 syyst\u00e4 sen analysointiin tarvitaan erityisi\u00e4\r\nBig data l\u00e4hestymistapoja, jotka hy\u00f6dynt\u00e4v\u00e4t tietokoneavusteisia ty\u00f6kaluja ja -prosesseja.\r\nBig data on termi joka kuvaa eritt\u00e4in suurta volyymia strukturoitua, osittain strukturoitua tai\r\nstrukturoimatonta dataa, joka on niin suuri ett\u00e4 sen prosessointi perinteisin tietokanta- tai\r\nohjelmistoteknisin ty\u00f6kaluin tai tekniikoin on vaivalloista. Nykyisin tekninen informaatio,\r\nkuten patentit, s\u00e4ilytet\u00e4\u00e4n datakokoelmissa, jotka eiv\u00e4t tue edistyneit\u00e4 Big data menetelmi\u00e4\r\nstrukturoida ja tulkita dokumentteja. Nousevassa Semanttisessa teknologiassa annotaatio,\r\nweb-haku, sek\u00e4 tulkinta ja koostaminen k\u00e4sitell\u00e4\u00e4n ontologia-pohjaisella semanttisella annotaatiolla.\r\nT\u00e4m\u00e4 tutkielma k\u00e4sittelee semanttista annotaatiota ja muita Big data menetelmi\u00e4\r\nja niiden perusedellytyksi\u00e4, sek\u00e4 tarkastelee nykyaikaisia semanttisen annotaation ja muiden\r\nBig data menetelmien j\u00e4rjestelmi\u00e4. Tapaustutkimuksena t\u00e4m\u00e4 tutkielma osoittaa, miten semanttista\r\nannotaatiota ja muita Big data tekniikoita voidaan hy\u00f6dynt\u00e4\u00e4 parantamaan prosesseja,\r\njoiden avulla ihmiset hakevat tietoa, tekev\u00e4t analyysi\u00e4 tai hakuja eritt\u00e4in suuresta\r\npatentti-informaation kokoelmasta.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted using Plone Publishing form by Phesto Mwakyusa (phenmwak) on 2017-10-23 13:27:03.498517. Form: Master's Thesis publishing form (https://kirjasto.jyu.fi/publish-and-buy/publishing-forms/masters-thesis-publishing-form). JyX data: [jyx_publishing-allowed (fi) =True]", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2017-10-23T13:27:04Z\r\nNo. of bitstreams: 2\r\nURN:NBN:fi:jyu-201710234047.pdf: 2171254 bytes, checksum: d089a7c4a26de0b892867d97a46b3c3d (MD5)\r\nlicense.html: 4300 bytes, checksum: 743f3d19b422e15d1e0bbdfbd9d15911 (MD5)", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2017-10-23T13:27:04Z (GMT). No. of bitstreams: 2\r\nURN:NBN:fi:jyu-201710234047.pdf: 2171254 bytes, checksum: d089a7c4a26de0b892867d97a46b3c3d (MD5)\r\nlicense.html: 4300 bytes, checksum: 743f3d19b422e15d1e0bbdfbd9d15911 (MD5)\r\n Previous issue date: 2017", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "1 verkkoaineisto (73 sivua)", "language": null, "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "semanttinen annotointi", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Data Mining", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Semantic annotation", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Patent information", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Semantic annotation and big data techniques for patent information processing", "language": null, "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-201710234047", "language": null, "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": 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